Abstract
Repetitive dengue fever outbreaks in Pakistan
have brought major concerns to the government authorities to
control this mosquito borne disease. Although dengue cases are
reported in many cities of Pakistan but Lahore has been the most
affected city during last few years. In 2011, dengue outbreaks in
Lahore are considered as the worst epidemic in the national
history. There is an urgent need to manage this disease
effectively. In order to keep the virus under control, it is also
required to explore the possible causes and factors that support
dengue virus to grow. In this study climatic and environmental
factors that may presumably promote the growth of virus are
selected and their spatial and temporal variations are correlated
with dengue cases. The objective of this paper is to develop a
geospatial dengue risk model to identify the risk prone areas by
linking these factors with dengue outbreaks using satellite data
and Geographical Information System (GIS) techniques. Satellite
images of SPOT-5, Landsat-TM and Google Earth are used in
this study to derive environmental and landuse parameters. The
model parameters used for this study are Land Surface
Temperature (LST), Normalized Difference Vegetation Index
(NDVI), Normalized Difference Water Index (NDWI), built-up
area, population, population density and precipitation. Ordinary
Least Square (OLS) and Geographical Weighted Regression
(GWR) analyses are performed to develop regression models
between dengue cases and other study parameters. Based on
study results, it is concluded that study parameters are not
suitable for OLS global model since no statistically strong model
can be found using OLS. GWR analysis is a form of linear
regression that can model spatially varying relationships between
variables. The GWR model shows that using population density
and built-up area as explanatory variables, the model can explain
77% of the variance in dengue incidences.
BILAL TARIQ, ARJUMAND Z. ZAIDI. (2015) Geo-statistical Dengue Risk Model Case Study of Lahore Dengue Outbreaks 2011, Journal of Space Technology , Volume 5, Issue 1.
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